Customer Reviews

Introduction to Probability, 2nd Edition

5 star:		(7)
4 star:		(1)
3 star:		(0)
2 star:		(0)
1 star:		(1)

 

 

Overall, this is an outstanding textbook. When one says a book is well written, it could just mean a fluidity sentence-to-sentence or paragraph-to-paragraph. This book has that, but much more importantly, it is organized well. It tells its story in digestible segments that introduce material at a consistent pace and consistent depth throughout. Because of a disciplined avoidance of unnecessary mathematical technicalities and flourishes, the book has a fast pace without being difficult to read. The end result is a solid grounding in the foundations of probability along with introductions to random processes and statistical inference in a remarkably concise volume.

This book is an introduction that requires only basic working knowledge of calculus. This influences the coverage. For example, the authors could easily go further on the topic of Markov chains by requiring just some basic knowledge of linear algebra. Similarly, with linear algebra it would be easy to cover estimation problems involving jointly Gaussian vectors. By keeping the mathematical prerequisites to a minimum, the book is made accessible to a broad audience, early in their education. It is certainly accessible across fields of science and engineering. It could also appeal to any reader who wants to understand some quantification of uncertainty, for example in business or public policy. While the authors are engineering professors, the techniques and examples are not disproportionately targeted to engineering.

This book is not a mathematics book. It does not expose the intricacies of the mathematical foundations of probability, and the typesetting does not include definition, theorem, or proof environments. This is not to say that the book is mathematically inaccurate; at worst, there are some lies of omission. All but the most mathematically-sophisticated readers benefit from this style in a first formal exposure to probability.

This book is also not a philosophical treatise: there is one page on the history of probability and one page on arguments between Bayesians and frequentists. Some probability books seem to be written for an audience that needs to be convinced to learn probability (``See, this result is surprising [or counterintuitive]!''). The present book does not waste its breath like this.

One of the tricks to keeping the book short and the main body text elementary is to include a lot of material in the end-of-chapter problems. The most important such content is provided through problems that have solutions included within the book. Solutions to most of the more routine problems are not included in the book, but they are

available for download on the publisher's website. Additional exercises are also available (for anyone, not just instructors) on the publisher's website. Because the authors have squeezed extra material in through the end-of-chapter problems, it may be a fair criticism to say that there aren't very many simple exercises for the reader to work through to learn the material. One way to find material freely online that is aligned with the textbook is to search for "6.041 site:mit.edu".

Some compromises in maintaining a reasonable length for the book show. The final two chapters, covering Bayesian and classical statistical inference, include many new concepts and terms. It is hard to absorb this material without many examples, and the examples in these chapters seem somewhat more difficult than those earlier in the book. Though these chapters comprise almost a quarter of the book, they are still only a brief introduction to statistical inference.

Any fundamental topic is the subject of many textbooks, and which books are best depends on the background and interests of the reader. Having skimmed various other textbooks while teaching a semester-long courses with this one six times, I have come to believe that there is a large audience for which this is the best available textbook. Readers with strong mathematical backgrounds may prefer more mathematical formality, and a thorough introduction to statistical inference requires follow on study, but these facts are not weaknesses of the present book.

Disclaimers: Both authors are my colleagues. While I have read several probability textbooks, this book (in both its editions) is the only one I have used in teaching.

This is an outstanding book that helps to make the subject of probability come alive. It is targeted primarily towards students in engineering, computer/information sciences, management sciences, and other disciplines where probability is applied. This means that it avoids the more advanced measure-theoretic aspects of the subject that can be found in other standard texts; however it manages to do so without any loss of mathematical rigor. Indeed, even those studying probability from a more theoretical standpoint may find this book useful as a supplementary resource; the writing style is friendly and lucid, and difficult concepts are explained and clarified through numerous carefully designed examples.

I believe the book will be valued by anyone seeking a clear understanding of the fundamental concepts of probability. It is a terrific resource for instructors looking for ways to illustrate probabilistic concepts to their students (this is the capacity in which I have used the book). With the addition of the chapters on statistical inference in the second edition, it is likely to be a valuable reference for practitioners as well, particularly those seeking to refresh the connections between statistical methods and basic probability. Overall, highly recommended.

I'm studying Operations Research so probability is incredibly important. I've taken 2 probability courses and one statistics course. This is, by far, one of the best probability textbooks I've used. The explanations are intuitive and clear, giving the reader a good fundamental understanding of important concepts. I've used Probability and Statistics for Scientists and Engineers (Ross) as well as Probability and Statistics (Degroot), and this book, for probability concepts, blows the two books away.

I used this book during an upper undergrad probability course in addition to the Ross book that was the main text for class. For someone without a strong math background, the Bersekas and Tsitsiklis text made probability theory understandable and easy to comprehend. I wouldn't have passed the class without this text. As a PhD candidate in Biology, I still refer to this text to help get through background material I am learning for my dissertation research. This is a great reference to have on hand if you are new to probability theory to help you get through a class and to continue using even after class. I highly recommend this book.

This book is an excellent introduction to probability and random variables. I'm currently using it for MIT's 6.431. The exposition and examples are very clear without any loss of mathematical rigor. I tried Ross' textbook, but I found that it got into way too many proofs for my taste. This book focuses on developing intuition for probabilistic models... and for that I give it 5 stars.

This book is generally excellent, with clear explanations and a good balance of rigor and practical application. You won't find proofs of everything, but you will find excellent guidance and intuition through the various topics, especially the fundamentals. The chapter on estimation, added for the second edition, is some of the most interesting material in the book, and covers both frequentist and bayesian estimation.

The only significant complaint I have is that certain topics are covered too briefly (such as the central limit theorem or stochastic processes). In the end, however, the terse coverage of certain topics is more than made up for by the fine handling of the fundamentals, and I unreservedly recommend the book for anybody studying the topic, especially for the first time.

This book is an excellent introduction to probability.

The text is clear and detail and full of interesting examples.

The proofs are usually easy too follow.

I have used this book as a "refresher" and I feel that I have acquire a deeper understanding on probability that I previously had.

This is the coursebook for a probability class for engineers I'm currently taking. The book does not offer enough explanation. The formatting is mildly helpful. However, there are not enough example problems. There are occasionally pictures in which only a caption is used to explain the solution to the problem. The examples are not easily related to the homework problems put forth in the book. This book does not help expand ones knowledge of solving problems, and should be heavily supplemented.

I am very satisfied with my order. The book I purchased from this seller was in near-perfect condition like the seller described on Amazon.com. I ordered the book on expedited shipping, and the book came within a few days. I definitely recommend buying things from this seller.